Characterizing Fire in Large Underground Ventilation Networks Using Machine Learning - SME Annual Meeting 2024

Underground mine accidents, such as mine fires, remain a health and safety risk to mine workers. Researchers at the National Institute for Occupational Safety and Health (NIOSH) are developing a data-driven, predictive model for characterizing the location and size of unknown underground fires. This study examines applying a machine learning-based model to predict fire size and location in a large underground metal mine based on hypothetical scenarios on the model performance. The results show that the size and location of an unknown fire can be determined with over 80% and 90% accuracy, respectively, and potentially help to reduce the risk of hazardous conditions for emergency response.